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Adaptive Image and Video Retargeting Technique Based on Fourier Analysis. Jun- Seong Kim, Jin-Hwan Kim, and Chang-Su Kim School of Electrical Engineering, Korea University, Seoul, Korea Reporter: Chia-Hao Hsieh Date: 20100316. Outline. Introduction Methods Simulation results.
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Adaptive Image and Video Retargeting Technique Based on Fourier Analysis Jun-Seong Kim, Jin-Hwan Kim, and Chang-Su Kim School of Electrical Engineering, Korea University, Seoul, Korea Reporter: Chia-Hao Hsieh Date: 20100316
Outline • Introduction • Methods • Simulation results
Introduction Original Scaled Cropped Retargeted
Methods • Partitioning • Scaling distortions • Adaptive scaling
Partitioning K = 10 in this work
Scaling distortions • z[n]: a row signal of length lk in the kth strip • Reduce the length by removing rk pixels to obtain a downsampled signal zd[n] • The sampling rate is reduced by a factor of (1-(rk/lk))π
Scaling distortions • The signal should be lowpass-filtered with a cutoff frequency ωc = (1-(rk/lk))π to avoid aliasing artifacts • Scaling distortions (The energy of the lost high frequency components) A smaller sk makes the exponential function decrease more quickly Can be approximated by Except for the dominant DC component
Scaling distortions Scaling distortion of the kth strip: Can be approximated by Except for the dominant DC component
Adaptive scaling R = Ws − Wt To minimize the sum of the distortions of strips Constrained optimization problem Can be solved by minimizing the Lagrangian cost function
Extension to video retargeting • Cut the volume into parallelepipeds along the time axis • Each parallelpiped is scaled down spatially Partitioning of a video sequence for horizontal resizing.
Conclusions • The proposed algorithm requires much less computations than the seam carving • Excellent temporal coherence without jitter artifacts